Validation of the FBMUX questionnaire for measuring communicative expression of UX sounds on 3 levels

Drawing on prior works that produced a communication model and parts of a standardized questionnaire for measuring meanings conveyed by UX sounds, the present contribution presents an empirical validation of the now finalized English-language FBMUX questionnaire instrument meant to measure UX sounds’ perceived communicative expression regarding status, appeal and brand. Thereto, a pool of 805 UX sounds stemming from varying industrial sectors was rated on the FBMUX during an online listening survey by 1406 consumers with differing gender, age, education and migration background from UK. Results of confirmatory factor analyses of acquired data demonstrate reliability, discriminant validity, as well as strong factorial invariance of the FBMUX across different consumer groups. Further analyses employing the FBMUX show differential understanding, familiarity and liking of UX sounds in the pool, dependent on consumers’ social position and industrial sector where the sounds are used. The resulting FBMSet-805 dataset can be employed in future works for training machine learning algorithms aiming at predicting UX sound understanding and liking.